class_docstr: Base class of HalfCheetah meta-environments.
  
  Code is adapted from
  https://github.com/tristandeleu/pytorch-maml-rl/blob/493e677e724aa67a531250b0e215c8dbc9a7364a/maml_rl/envs/mujoco/half_cheetah.py
  
  Which was in turn adapted from
  https://github.com/cbfinn/maml_rl/blob/9c8e2ebd741cb0c7b8bf2d040c4caeeb8e06cc95/rllab/envs/mujoco/half_cheetah_env_rand.py
  
  Args:
      task (dict): Subclass specific task information.
docstr: Get a low-dimensional observation of the state.
  
  Returns:
      np.ndarray: Contains the flattened angle quaternion, angular
          velocity quaternion, and cartesian position.
docstr_tok: ["Get","a","low-dimensional","observation","of","the","state",".","Returns",":","np.ndarray",":","Contains","the","flattened","angle","quaternion",",","angular","velocity","quaternion",",","and","cartesian","position","."]
code: def _get_obs(self):
      """Get a low-dimensional observation of the state.
  
      Returns:
          np.ndarray: Contains the flattened angle quaternion, angular
              velocity quaternion, and cartesian position.
  
      """
      return (
          np.concatenate(
              [
                  self.sim.data.qpos.flat[1:],
                  self.sim.data.qvel.flat,
                  self.get_body_com("torso").flat,
              ]
          )
          .astype(np.float32)
          .flatten()
      )
  
file_path: garage/src/garage/envs/mujoco/half_cheetah_env_meta_base.py
imports: from gym.envs.mujoco import HalfCheetahEnv
  import numpy
  from garage import EnvSpec
label_desc: Use image node_id 2 for calling the HalfCheetahEnvMetaBase obj's underlying member method code with example usage: obj._get_obs() and returns: np